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Senior ML Engineer

Зарплата

от 5000 $

Местоположение и тип занятости

Полный рабочий деньМожно удаленно

Описание вакансии

О компании и команде

The company develops a system capable of semantic processing of programming code, e.g., code analysis, transformation, and synthesis, as well as operating a computational environment. The approach combines explicit knowledge representation in discrete structures with ML-assisted algorithms to manipulate those structures. The system we design should be able to follow the reasoning trajectory and examine the internal logic; identify a lack of information and interact with external sources; incorporate new knowledge at later stages equally inexpensive as at the initial ones.

Ожидания от кандидата

What we need help with

1. Running open-sourced models on our hardware.

2. Fine-tuning models for our needs.

3. Building pipeline for distributed training.

4. Integrating models with the rest of our systems.

5. Staying on top of architectures and frameworks.

6. Analysing and suggesting improvements for datasets.

Who we are looking for

1. In-depth knowledge of: Machine Learning, Deep Learning, Training customisation, ML frameworks.

2. Known architectures: Transformer, LLM, GNN, Autoencoders.

3. Languages: Python, Rust, C++

4. Frameworks: PyTorch, TensorFlow.

5. Bachelor’s degree or higher.

6. English C1 or higher.

A strong advantage would be

1. Agile Experience. We use a management approach that is close to Agile. Among others, we use guided continuous improvement, task prioritisation, sprints, value delivery, and focus on commitment.

2. Abstract thinking.

3. Infrastructure Tools like Notion, Slack, Zotero, Shortcut, Miro, Git.

Условия работы

Not just an ML

People tend to think that AI is solely Machine Learning, like ChatGPT (or DALL-E 2, or Microsoft Bing, or ChatSonic). We are building our solution on an alternative architecture which incorporates ML as a part.

Going beyond

We put much effort into profound research and development of new underlying technologies rather than reusing existing ones. We like to explore unfairly neglected and non-conventional approaches to AI.

Safety and Alignment

We want to be responsible in our research and development. We don't turn our noses up at AI safety research and take the issue of alignment seriously.

Good Salary

That is, of course, a very basic condition. We want our colleagues to be healthy, happy and recreated. We have an individual approach to the formation of employees salaries. The level and conditions are agreed on a case-by-case basis with each candidate following the interview.

Hybrid Remote

Our team members work from both the office and homes all around the world. We are OK with that. However, we like to gather sometimes at the office to get on the same page.

Flexible Schedule

Outside scheduled team meetings, teammates are free to work on their tasks independently. When to work is a personal choice. Just do not overwork – that is inefficient.

Low Bureaucracy

What we value most are performance and results, not a strict process following. However, metrics, processes, and documentation are important too. We just keep their priorities low.